Vuk Ercegovac

20030014396, Jan 16, 2003

Jul 16, 2001

09/906502

Navin Kabra - Pune, IN
Raghu Ramakrishnan - Madison WI, US
Uri Shaft - San Leandro CA, US
Vuk Ercegovac - San Francisco CA, US

G06F007/00

707/003000

A unified database/text retrieval system converts exact database type queries into text inclusion type queries suitable for text retrieval systems through the use of pseudo keywords. Boolean combination of the text inclusion type query elements may be readily manipulated for optimization and applied to a unified index for rapid search results. Absolute relevance values and relevance multiplier values may be added to the query elements to provide a relevance-based sorting not only of text but also of exact match type search results. Relevance values may be deduced automatically from a variety of sources.

20090228528, Sep 10, 2009

Mar 6, 2008

12/043858

Vuk Ercegovac - Campbell CA, US
Vanja Josifovski - Los Gatos CA, US
Ning Li - Cary NC, US
Mauricio Mediano - Cupertino CA, US
Eugene J. Shekita - San Jose CA, US

International Business Machines Corporation - Armonk NY

G06F 17/30

707203, 707E17005

A system, method, and computer program product for updating a partitioned index of a dataset. A document is indexed by separating it into indexable sections, such that different ones of the indexable sections may be contained in different partitions of the partitioned index. The partitioned index is updated using an updated version of the document by updating only those sections of the index corresponding to sections of the document that have been updated in the updated version.

20110320184, Dec 29, 2011

Jun 29, 2010

12/826077

Kevin S. Beyer - San Francisco CA, US
Vuk Ercegovac - Campbell CA, US
Peter Haas - San Jose CA, US
Eugene J. Shekita - San Jose CA, US
Fei Xu - Bellevue WA, US

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

G06F 9/45

703 22

Systems and associated methods for highly parallel processing of parameterized simulations are described. Embodiments permit processing of stochastic data-intensive simulations in a highly parallel fashion in order to distribute the intensive workload. Embodiments utilize methods of seeding records in a database with a source of pseudo-random numbers, such as a compressed seed for a pseudo-random number generator, such that seeded records may be processed independently in a highly parallel fashion. Thus, embodiments provide systems and associated methods facilitating quicker data-intensive simulation by enabling highly parallel asynchronous simulations.

20120179684, Jul 12, 2012

Jan 12, 2011

13/005425

Alfredo Alba - Morgan Hill CA, US
Chad E. DeLuca - San Jose CA, US
Vuk Ercegovac - Campbell CA, US
Thomas D. Griffin - Campbell CA, US
Jun Rao - San Jose CA, US
Asim V. Singh - San Jose CA, US
Kevin B. Wang - Mountain View CA, US

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

G06F 17/30

707738, 707739, 707E17002, 707E17046

A computer program product for an indexer-agnostic index building system includes a computer readable storage medium to store a computer readable program, wherein the computer readable program, when executed on a computer, causes the computer to perform operations for creating a semantically aggregated index. The operations include: extracting documents from a data source, wherein each document includes a data object; distributing the documents to a plurality of processing nodes within the system; for each node: indexing the data objects for each document into fields using semantic rules; and grouping indexed data objects for related fields by: classifying the documents into logical groups based on the semantic rules; and creating a searchable index shard for related logical groups.

20120254089, Oct 4, 2012

Mar 31, 2011

13/077586

Alfredo Alba - Morgan Hill CA, US
Chad E. DeLuca - San Jose CA, US
Vuk Ercegovac - Campbell CA, US
Thomas D. Griffin - Campbell CA, US
Jun Rao - San Jose CA, US
Eugene J. Shekita - San Jose CA, US
Asim V. Singh - San Jose CA, US
Yuanyuan Tian - San Jose CA, US
Kevin B. Wang - Mountain View CA, US

International Business Machines Corporation - Armonk NY

G06N 5/02

706 47

Embodiments of the invention relate to building a distributed reverse semantic index. In one general embodiment a plurality of documents are received with each document having at least one defined rule and or semantic. The documents are distributed among a plurality of nodes of a system. The documents are processed in a generally parallel fashion. Processing the documents includes processing text data of each of the document and breaking each document into fields to index the text data to create index data by deferring how to categorize the text data based upon the defined rule and or semantics. The indexed data is combined back together to create an indexer-agnostic semantic index including a plurality of the semantic index shards and to semantically classify the documents based on the index shards into groups based on document type to create the distributed reverse semantic index.

20120311581, Dec 6, 2012

May 31, 2011

13/149312

Andrey Balmin - San Jose CA, US
Kevin Scott Beyer - San Francisco CA, US
Vuk Ercegovac - Campbell CA, US
Rares Vernica - Irvine CA, US

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

G06F 9/46

718100

Described herein are methods, systems, apparatuses and products for adaptive parallel data processing. An aspect provides providing a map phase in which at least one map function is applied in parallel on different partitions of input data at different mappers in a parallel data processing system; providing a communication channel between mappers using a distributed meta-data store, wherein said map phase comprises mapper data processing adapted responsive to communication with said distributed meta-data store; and providing data accessible by at least one reduce phase node in which at least one reduce function is applied. Other embodiments are disclosed.

20120323551, Dec 20, 2012

Aug 27, 2012

13/595446

Kevin S. Beyer - San Francisco CA, US
Vuk Ercegovac - Campbell CA, US
Peter Haas - San Jose CA, US
Eugene J. Shekita - San Jose CA, US
Fei Xu - Bellevue WA, US

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

G06F 9/45

703 22

Systems and associated methods for highly parallel processing of parameterized simulations are described. Embodiments permit processing of stochastic data-intensive simulations in a highly parallel fashion in order to distribute the intensive workload. Embodiments utilize methods of seeding records in a database with a source of pseudo-random numbers, such as a compressed seed for a pseudo-random number generator, such that seeded records may be processed independently in a highly parallel fashion. Thus, embodiments provide systems and associated methods facilitating quicker data-intensive simulation by enabling highly parallel asynchronous simulations.

20120323919, Dec 20, 2012

Aug 27, 2012

13/595761

Alfredo Alba - Morgan Hill CA, US
Chad E. DeLuca - San Jose CA, US
Vuk Ercegovac - Campbell CA, US
Thomas D. Griffin - Campbell CA, US
Jun Rao - San Jose CA, US
Eugene J. Shekita - San Jose CA, US
Asim V. Singh - San Jose CA, US
Yuanyuan Tian - San Jose CA, US
Kevin B. Wang - Mountain CA, US

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

G06F 17/30

707738, 707740, 707E17083

Embodiments of the invention relate to building a distributed reverse semantic index. In one general embodiment a plurality of documents are received with each document having at least one defined rule and or semantic. The documents are distributed among a plurality of nodes of a system. The documents are processed in a generally parallel fashion. Processing the documents includes processing text data of each of the document and breaking each document into fields to index the text data to create index data by deferring how to categorize the text data based upon the defined rule and or semantics. The indexed data is combined back together to create an indexer-agnostic semantic index including a plurality of the semantic index shards and to semantically classify the documents based on the index shards into groups based on document type to create the distributed reverse semantic index.